Works (16)

Updated: July 5th, 2023 15:50

2015 article

Advancing Inverse Sensitivity/Uncertainty Methods for Nuclear Fuel Cycle Applications

Arbanas, G., Williams, M. L., Leal, L. C., Dunn, M. E., Khuwaileh, B. A., Wang, C., & Abdel-Khalik, H. (2015, January). NUCLEAR DATA SHEETS, Vol. 123, pp. 51–56.

TL;DR: It is shown how the IS/UQ method could be applied to systematic and statistical uncertainties in a self-consistent way and how it could be used to optimize uncertainties of IBEs and differential cross section data simultaneously. (via Semantic Scholar)
UN Sustainable Development Goal Categories
7. Affordable and Clean Energy (OpenAlex)
Source: Web Of Science
Added: August 6, 2018

2015 article

Subspace-based Inverse Uncertainty Quantification for Nuclear Data Assessment

Khuwaileh, B. A., & Abdel-Khalik, H. S. (2015, January). NUCLEAR DATA SHEETS, Vol. 123, pp. 57–61.

By: B. Khuwaileh n & H. Abdel-Khalik n

TL;DR: A subspace-based algorithm for inverse sensitivity/uncertainty quantification (IS/UQ) has been developed to enable analysts account for all sources of nuclear data uncertainties in support of target accuracy assessment-type analysis. (via Semantic Scholar)
UN Sustainable Development Goal Categories
Source: Web Of Science
Added: August 6, 2018

2014 conference paper

Development of subspace-based hybrid Monte Carlo-deterministic algorithms for reactor physics calculations

Proceedings of the 21st International Conference on Nuclear Engineering - 2013, vol 6.

By: Q. Zhang & H. Abdel-Khalik

Source: NC State University Libraries
Added: August 6, 2018

2014 journal article

Global variance reduction for Monte Carlo reactor physics calculations

NUCLEAR ENGINEERING AND DESIGN, 280, 76–85.

By: Q. Zhang n & H. Abdel-Khalik n

TL;DR: It is found that using the SUBSPACE method significant speedup can be achieved over the state of the art FW-CADIS method, and it is believed this work will become a major step on the way of leveraging the accuracy of MC calculations for assembly calculations. (via Semantic Scholar)
UN Sustainable Development Goal Categories
7. Affordable and Clean Energy (OpenAlex)
Source: Web Of Science
Added: August 6, 2018

2014 conference paper

Stochastic higher-order generalized perturbation theory for neutron diffusion and transport calculations

Proceedings of the 21st International Conference on Nuclear Engineering - 2013, vol 6.

By: C. Wang n & H. Abdel-Khalik n

TL;DR: This manuscript will be focus on presenting the own developments of stochastic higher-order generalized perturbation theory to address the explosion in the computational load burden of large-scale system with large number of Degrees of Freedom. (via Semantic Scholar)
UN Sustainable Development Goal Categories
16. Peace, Justice and Strong Institutions (OpenAlex)
Source: NC State University Libraries
Added: August 6, 2018

2013 journal article

Exact-to-precision generalized perturbation theory for eigenvalue problems

NUCLEAR ENGINEERING AND DESIGN, 256, 130–140.

By: C. Wang n & H. Abdel-Khalik n

UN Sustainable Development Goal Categories
Source: Web Of Science
Added: August 6, 2018

2013 journal article

Hybrid biasing approaches for global variance reduction

APPLIED RADIATION AND ISOTOPES, 72, 83–88.

By: Z. Wu n & H. Abdel-Khalik n

author keywords: Hybrid Monte Carlo; DT approach; FW-CADIS; Gaussian process; Global variance reduction
TL;DR: A new variant of Monte Carlo-deterministic (DT) hybrid variance reduction approach based on Gaussian process theory is presented and compared with Forward-Weighted Consistent Adjoint Driven Importance Sampling approach implemented in the SCALE package from Oak Ridge National Laboratory. (via Semantic Scholar)
UN Sustainable Development Goal Categories
Source: Web Of Science
Added: August 6, 2018

2013 journal article

Overview of hybrid subspace methods for uncertainty quantification, sensitivity analysis

ANNALS OF NUCLEAR ENERGY, 52, 28–46.

By: H. Abdel-Khalik n, Y. Bang n & C. Wang n

author keywords: Uncertainty quantification; Sensitivity analysis; Variational methods; Sampling methods
TL;DR: The manuscript intends to serve as a pedagogical presentation of the material to young researchers and practitioners with little background on the subjects to address the explosion in the computational overhead required when handling real-world complex engineering systems. (via Semantic Scholar)
UN Sustainable Development Goal Categories
Source: Web Of Science
Added: August 6, 2018

2013 journal article

Projection-based second order perturbation theory

ANNALS OF NUCLEAR ENERGY, 52, 80–85.

By: Y. Bang n & H. Abdel-Khalik n

author keywords: Nonlinear sensitivity analysis; Higher order perturbation theory; Projection
UN Sustainable Development Goal Categories
Source: Web Of Science
Added: August 6, 2018

2012 journal article

Adjoint-based sensitivity analysis for multi-component models

NUCLEAR ENGINEERING AND DESIGN, 245, 49–54.

By: H. Abdel-Khalik n

TL;DR: This manuscript presents a hybrid approach to enable the transfer of sensitivity information between the various components in an efficient manner that precludes the need for a global sensitivity analysis procedure. (via Semantic Scholar)
UN Sustainable Development Goal Categories
Source: Web Of Science
Added: August 6, 2018

2012 journal article

GENERALIZED PERTURBATION THEORY-FREE SENSITIVITY ANALYSIS FOR EIGENVALUE PROBLEMS

NUCLEAR TECHNOLOGY, 179(2), 169–179.

By: C. Kennedy n, C. Rabiti* & H. Abdel-Khalik n

author keywords: generalized perturbation theory; reduced order modeling; sensitivity analysis
TL;DR: This paper introduces a reduced-order modeling approach based on subspace methods that requires the solution of the fundamental adjoint equations but allows the generation of response sensitivities without the need to set up GPT equations, and that provides an estimate of the error resulting from the reduction. (via Semantic Scholar)
UN Sustainable Development Goal Categories
Source: Web Of Science
Added: August 6, 2018

2012 journal article

Hybrid reduced order modeling applied to nonlinear models

INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING, 91(9), 929–949.

By: Y. Bang n, H. Abdel-Khalik n & J. Hite n

author keywords: nonlinear sensitivity analysis; reduced order modeling; subspace methods
UN Sustainable Development Goal Categories
Source: Web Of Science
Added: August 6, 2018

2012 journal article

State-Based Adjoint Method for Reduced Order Modeling

TRANSPORT THEORY AND STATISTICAL PHYSICS, 41(1-2), 101–132.

By: Y. Bang n, C. Wang n & H. Abdel-Khalik n

author keywords: initial conditions perturbation; reduced order modeling; subspace reduction; adjoint methods
Source: Web Of Science
Added: August 6, 2018

2011 article

Exact-to-precision generalized perturbation theory for source-driven systems

Wang, C., & Abdel-Khalik, H. S. (2011, December). NUCLEAR ENGINEERING AND DESIGN, Vol. 241, pp. 5104–5112.

By: C. Wang n & H. Abdel-Khalik n

TL;DR: New developments to perturbation theory are intended to extend its applicability to estimate, with quantifiable accuracy, the exact variations in all responses calculated by the model with respect to all possible perturbations in the model's input parameters. (via Semantic Scholar)
UN Sustainable Development Goal Categories
Source: Web Of Science
Added: August 6, 2018

2011 journal article

Many-Group Cross-Section Adjustment Techniques for Boiling Water Reactor Adaptive Simulation

NUCLEAR SCIENCE AND ENGINEERING, 169(1), 40–55.

By: M. Jessee n, P. Turinsky n & H. Abdel-Khalik n

UN Sustainable Development Goal Categories
6. Clean Water and Sanitation (OpenAlex)
Source: Web Of Science
Added: August 6, 2018

2009 journal article

A comparative study of ZPR-6/7 with MCNP/5 and MC2-2/REBUS

ANNALS OF NUCLEAR ENERGY, 36(7), 995–997.

By: M. Iqbal n, H. Abdel-Khalik n & P. Turinsky

UN Sustainable Development Goal Categories
7. Affordable and Clean Energy (OpenAlex)
Source: Web Of Science
Added: August 6, 2018

Citation Index includes data from a number of different sources. If you have questions about the sources of data in the Citation Index or need a set of data which is free to re-distribute, please contact us.

Certain data included herein are derived from the Web of Science© and InCites© (2024) of Clarivate Analytics. All rights reserved. You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.